1. Fundamental Issues. 2. Basic Analytical Procedures. 3. Assessing Risk Factors. 4. Confounding And Interaction. 5. Cohort Studies. 6. Case-Control Studies. 7. Intervention Studies. 8. Sample Size Determination. 9. Modeling Quantitative Outcome Variables. 10. Modeling Binary Outcome Data. 11. Modeling Follow-Up Data. 12. Meta-Analysis. 13. Risk Scores And Clinical Decision Rules. 14. Computer-Intensive Methods.
A?companion book for Epidemiology study design and data analysis 3rd edition. Aims to equip with sufficient knowledge to use R for practising epidemiology. Reworks the examples in epidemiology study design and data analysis using R, presenting the code followed by an explanation and its result.
Dr Ajith R worked as a primary care physician for 21 years after completing graduation. He has a postgraduate diploma in clinical pathology and has completed India Epidemic Intelligence Service Training.
R Companion to Epidemiology: Study Design and Data Analysis is a companion volume to the classic textbook by Mark Woodward, Epidemiology: Study Design and Data Analysis, Third Edition. It aims to equip the reader with sufficient knowledge to use R for practising epidemiology. Towards this aim, it reworks the examples in the textbook, presenting the code followed by an explanation and its result.
Key Features:
- Almost all of the numerical examples in the textbook are reworked in R
- R code is introduced in small portions and explained thoroughly
- Complexity of introduced code is increased only gradually
- More than 300 commands spanning more than 40 libraries are introduced
The book is intended primarily to be used as a supplement to the telóZ